Geometric optimization on optical performance of parabolic trough solar collector systems using particle swarm optimization algorithm

In this paper, an optimization model on optical performance of parabolic trough solar collector (PTC) systems is developed, based on the particle swarm optimization (PSO) algorithm and the Monte Carlo ray-tracing (MCRT) method. Since the computing time of a single MCRT simulation is always very critical to the whole optimization process and even to the feasibility of the optimization analysis if it is very time-consuming. Therefore, a MCRT runtime reduction method (RRM) was firstly proposed, by making a reasonable trade-off between the computational accuracy and the computing cost. Subsequently, the RRM was checked using well known statistical indices, due to the random number generation in the MCRT simulation and the statistical nature of the MCRT methodology. It is very significant that the corresponding calculation amount and computing time of a PTC MCRT simulation reduce by orders of magnitude and thus make the whole population-based PSO optimization process relative much feasible. Then a preliminary PSO-MCRT optimization analysis was carried out for an existing PTC system with known optimal optical performance, as it can be used to compare with the optimization results directly and thus to validate the PSO-MCRT optimization model. It is revealed that optimization results agree well with the reference data (Cheng et al., 2014), proving that the PSO-MCRT method and model used in the present study are feasible and reliable. In addition, error analysis and some further studies based on this proposed model are also discussed.